Chapter 1 · Chapter 1: Introducing GIS and health applications 5 Digital map infrastructure GIS is...

Chapter 1Introducing GIS and health applications

Objectives• Define GIS• Define spatial data for graphic and image map layers• Review the national infrastructure for spatial data• Review the unique capabilities of GIS• Demonstrate how GIS can be used for health applications• Introduce ArcGIS and its user interface• Introduce online GIS tools

Geographic information systems (GIS) is a technology that has unique and valuable applications for policy makers, planners, and managers in many fields, including public health and health care. GIS health applications include an academic organization’s use of GIS for medical research, a hospital or managed-care organization’s improved delivery of health-care services, and a public health department’s use of mapping and spatial statistics for disease surveillance and analysis. GIS software and applications allow visualization and processing of data in ways that were not possible in the past. The purpose of this book is to provide hands-on experience with the use of ArcGIS for Desktop software in the context of health applications. You need no previous experience using GIS.

This chapter describes GIS and its inputs and special capabilities and follows with a discussion of health issues and GIS applications. We also preview the upcoming tutorials in this book, and then use short tutorials in this chapter to introduce you to the use of ArcGIS software.

What is GIS?GIS is computer technology that engages geographers, computer scientists, social scientists, planners, engineers, and others in spatially analyzing issues. Consequently, it has been defined from several different perspectives (see Clarke 2003). We prefer a definition that emphasizes GIS as an information system:

Part 1GIS benefits and map basics

2 Chapter 1: Introducing GIS and health applications

labels for the names of states and cities come from tables of attribute records associated with each map layer. You will revisit this map in tutorials 1-3 and 1-4 in this chapter where you will use ArcGIS to explore map layers and spatial pat-terns of cancer mortality.

Raster maps are stored in standard digital image formats, such as tagged image file format (TIFF) and Joint Photographic Experts Group (JPEG) files. An image file is a rectangular array, or raster, of very small, square pixels. Each pixel, or cell, has a single value and solid color and corresponds to a small, square area on the ground, from 6 in. to 3 ft on a side for high-resolution images. Accompanying the image files are world files that provide georeferencing data, including the upper-left pixel’s location coordinates and the width of each pixel in ground units. Using world file information, GIS software can assemble individual raster datasets into larger areas and overlay them with aligned vector datasets.

Viewed on a computer screen or on a paper map, a raster map can provide a detailed backdrop of physical features. In figure 1.2, an aerial photograph over-laid with vector map layers shows locations where serious injuries of child pedestrians occurred in relation to public parks that have playgrounds. The two boundaries surrounding the parks are 600 ft and 1,200 ft buffers used to study injury rates near parks. You will explore the GIS data behind this map in depth in

GIS is a system for input, storage, processing, and retrieval of spatial data. Except for the additional word “spatial,” this is a standard definition of an information sys-tem. Spatial components include a digital map infrastructure, GIS software with unique functionality that focuses on location, and new mapping applications for organizations of all kinds. Definitions of these distinctive aspects of GIS follow.

Spatial dataSpatial data includes the locations and shapes of geographic features, in the form of either vector or raster data. Vector maps have features drawn using points, lines, and polygons to represent discrete geographic objects such as automobile accident locations, streets, and counties. (A polygon is a closed area that has a boundary consisting of connected straight lines.) Raster maps are generally aer-ial photographs, satellite images, or representations of surfaces such as elevation, which are used to represent continuous geographies.

For example, figure 1.1 is a vector map that has three polygon map layers (state and county boundaries and lakes), a line layer of rivers, and a point layer of cities that have populations of 250,000 or more. The state and county boundaries are coterminous — that is, they share boundaries and do not overlap each other. Color fill is used within the county polygons to show the mortality of lung cancer for white males. This map has some striking geographic patterns that are discussed later in this chapter.

Associated with individual point, line, or polygon features are data records that provide identifying and descriptive data attributes. For example, in figure 1.1, the

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Figure 1.1 Lung cancer mortality per 100,000 white males, 2000 – 2004.

3Chapter 1: Introducing GIS and health applications

labels for the names of states and cities come from tables of attribute records associated with each map layer. You will revisit this map in tutorials 1-3 and 1-4 in this chapter where you will use ArcGIS to explore map layers and spatial pat-terns of cancer mortality.

Raster maps are stored in standard digital image formats, such as tagged image file format (TIFF) and Joint Photographic Experts Group (JPEG) files. An image file is a rectangular array, or raster, of very small, square pixels. Each pixel, or cell, has a single value and solid color and corresponds to a small, square area on the ground, from 6 in. to 3 ft on a side for high-resolution images. Accompanying the image files are world files that provide georeferencing data, including the upper-left pixel’s location coordinates and the width of each pixel in ground units. Using world file information, GIS software can assemble individual raster datasets into larger areas and overlay them with aligned vector datasets.

Viewed on a computer screen or on a paper map, a raster map can provide a detailed backdrop of physical features. In figure 1.2, an aerial photograph over-laid with vector map layers shows locations where serious injuries of child pedestrians occurred in relation to public parks that have playgrounds. The two boundaries surrounding the parks are 600 ft and 1,200 ft buffers used to study injury rates near parks. You will explore the GIS data behind this map in depth in

Figure 1.2 Locations of serious injuries to child pedestrians in eastern Pittsburgh, Pennsylvania.

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chapters 4 and 7, where you will download similar orthoimagery and create and use buffers similar to those in figure 1.2.

Map layers have geographic coordinates, projections, and scale. Geographic coordinates for the nearly spherical world are measured in polar coordinates, and the angles of rotation are measured in degrees, minutes, and seconds, or decimal degrees. The (0,0) origin of the coordinate system is generally taken as the inter-section of the equator and the prime meridian (great circle), which passes through the poles and an observatory in Greenwich, England. Latitude is measured north and south for up to 90 degrees in each direction. Longitude is measured to the east and west of the origin for up to 180 degrees in each direction.

The world is not quite a sphere because the poles are slightly flattened and the equator is slightly bulged out. The world’s surface is better modeled by a spheroid, which has elliptical cross sections and two radii, instead of the one radius of a sphere. The mathematical representation of the world as a spheroid is called a datum; for example, a datum commonly used for North America is North American Datum of 1983 (NAD 1983). If you use the same projection but two dif-ferent datums for your maps, each corresponding map will have small but notice-able differences in location.

A point, line, or polygon feature on the surface of the world is on a three- dimensional spheroid, whereas features on a paper map or computer screen are on a flat surface. The mathematical transformation of a world feature into a flat map is called a projection. There are many projections, some of which you will use in chapter 4. Each projection has its own rectangular coordinate system and a (0,0) origin conveniently located so that coordinates are positive and have dis-tance units, usually in feet or meters.

All projections necessarily cause distortion of direction, shape, area, or length in some combination. So-called conformal projections preserve shape at the expense of distorting area. Some examples are the Mercator cylindrical and Lam-bert conic projections. Equal-area projections are the opposite of conformal pro-jections: They preserve area while distorting shape. An example is the Albers equal-area projection (Clarke 2003, 42 – 44).

Map scale is often stated as a unitless, representative fraction; for example, 1:24,000 is a map scale where 1 in. on the map represents 24,000 in. on the ground, and any distance units can be substituted for inches. Small-scale maps have a vantage point far above the earth and large-scale maps are zoomed in on rela-tively small areas. Distortions are considerable for small-scale maps but negligi-ble for large-scale maps relative to policy, planning, and research applications.

GIS maps are composites of overlying map layers. For large-scale maps such as figure 1.2, the bottom layer can be a raster map that has one or more vector layers on top, placed in order so that smaller or more important features are on top and not covered up by larger contextual features. Small-scale maps, such as figure 1.1, often consist solely of vector-map layers. Each vector layer consists of a homogeneous type of feature — points, lines, or polygons.


Digital map infrastructureGIS is perhaps the only information technology that requires a major digital infrastructure. The map layers of the infrastructure are referred to as basemaps — namely, a collection of standards, codes, and data designed, built, and main-tained by government. Vendors provide valuable enhancements to the digital map infrastructure, but for the most part, it is a public good financed by tax dol-lars. Without this infrastructure, GIS would not be a viable technology.

The National Spatial Data Infrastructure (NSDI), developed by the Federal Geo-graphic Data Committee (FGDC at http://www.fgdc.gov), incorporates policies, standards, and procedures that allow organizations to produce and share geo-graphic data. The Geospatial One-Stop website (http://geo.data.gov/geoportal), which is part of the NSDI, provides access to spatial data. Websites change often. The websites noted in this book could be named differently or redirected to dif-ferent sites, but the information will still be available if you search for it. GIS pro-vides a way to use this wealth of publicly available data in your own studies.

Perhaps the most useful spatial data for health applications comes from the US Census Bureau in the form of TIGER/Line maps. These maps are available by state and county for many classes of layers. These classes, and examples of each, include the following:

• Political: states, counties, county subdivisions (towns and cities), and voting districts

• Statistical: census tracts, block groups, and blocks• Administrative: ZIP Codes and school districts• Physical: highways, streets, rivers, streams, lakes, and railroadsYou can download TIGER/Line map layers in GIS-ready formats at no cost from

the US Census Bureau website (http://www.census.gov). Steps for doing so are included in chapter 5.

Census data that corresponds to TIGER/Line maps of statistical boundaries is tabulated by census-area codes and American National Standards Institute (ANSI) codes (http://www.census.gov/georeference/ansi.html). ANSI codes are “a standardized set of numeric or alphabetic codes issued by the American National Standards Institute (ANSI) to ensure uniform identification of geo-graphic entities through all federal government agencies,” according to the ANSI website. Data from the decennial census is available at no cost from the Census Bureau. Steps for downloading census data and preparing it for GIS use with TIGER/Line maps are included in chapter 5.

The US Geological Survey (http://www.usgs.gov/aboutusgs/) is the “nation’s largest water, earth, and biological science and civilian mapping agency . . . [and it] collects, monitors, analyzes, and provides scientific understanding about natural resource conditions, issues, and problems,” according to the USGS web-site. Among its products that are useful for health applications are national map orthoimagery aerial photographs (such as the one used in figure 1.2). Full national coverage of the most recent national map orthoimagery is available


from USGS via The National Map at http://viewer.nationalmap.gov/viewer/. Steps for downloading USGS maps are included in chapter 4.

Local governments provide many of the large-scale map layers in the United States, and most features in this data are smaller than a city block. This data includes deeded land parcels and corresponding real property data files on land parcels, structures, owners, building roof footprints, and pavement digitized from aerial photographs. You can often obtain such map layers and data for nominal prices from local governments. Some local health departments provide limited health data.

Unique capabilities of GISMaps were historically made for reference purposes. Street maps, atlases, and USGS topographic maps are all reference maps. It wasn’t until the advent of GIS, however, that analytic mapping became widely possible. For analytic mapping, an analyst collects and compiles related map layers, builds a database, and then uses GIS functionality to provide information for understanding or solving a problem. Before GIS, analytic mapping was limited to organizations such as city planning departments. Analysts did not have digital map layers, so they made hard-copy drawings on acetate sheets that could be overlaid and switched in and out to show before-and-after maps for a new facility such as a baseball stadium or a hospital. Using GIS, however, anyone can easily add, subtract, turn on and off, and modify map layers in an analytic map composition. This capacity has led to a revolution in geography and an entirely new tool for organizations of all kinds.

As figures 1.1 and 1.2 show, maps use symbols, which are defined in map leg-ends. Graphical elements of symbols include fill color, pattern, and boundaries for polygons; width, color, and type (solid, dashed, curved) for lines; and shape, color, and outline for points. A GIS analyst does not individually apply symbols to features, but applies and renders a layer at a time based on attribute values asso-ciated with geographic features.

For example, given a code attribute for schools that has the values “public,” “private,” and “parochial,” a GIS analyst can choose a green, circular, 10-point marker for public schools; a blue, square, 8-point marker for private schools; and an orange, triangular, 8-point marker for parochial schools. These three steps render all schools in a map layer by the desired point markers.

Similarly, we created the color-shaded county map layer in figure 1.1 based on an attribute that provides the lung cancer mortality rate of white males by county. A map that uses fill color in polygons for coding is called a choropleth map. In this case, it shows an equal-interval numeric scale, rendered using a gray monochromatic color scale. The darker the shade of gray, the higher the interval of the numeric scale. By making selections and setting parameters, the GIS analyst accomplishes all this coding and rendering using a simple graphic user interface (GUI).

Most organizations generate or collect data that includes street addresses, ZIP Codes, or other georeferences. GIS is able to spatially enable this data — that is, add geographic coordinates or make data records joinable to boundary maps.


Geocoding, also known as address matching, uses street addresses as input and assigns point coordinates to address records on or adjacent to street centerlines, such as in the TIGER/Line street maps. Geocoding uses a sophisticated program that has built-in intelligence — similar to that of a postal delivery person deliver-ing your mail — that can interpret misspellings, variations in abbreviations, and rearrangement of certain address components.

Policy, planning, and research activities often require data aggregated over space and time, rather than individual points. For example, in a study of demand patterns for locating a satellite medical clinic, it may be desirable to aggregate patient residence data to counts per census tract or ZIP Code boundaries for a recent year. GIS has the unique capacity to determine the areas in which points lie, using a spatial join or overlay function that allows the analyst to count points or summarize their attributes by area, using sums or averages.

This leads to the last GIS capability to be described in this section, proximity analysis. As an example, we conducted a study to determine whether the decline in the use of senior centers was affected by the distance from the seniors’ res-idences (Johnson et al. 2005). We geocoded the senior centers that provided human services and where the senior citizens lived, placing them as points on a map, and included the total target population using census data by city block. Then we used ArcGIS to create buffers around the facilities using a radius of 0.5 mi, 1 mi, 1.5 mi, 2 mi, and so on. We used spatial joins to assign buffer identi-fiers to residence points and blocks, count clients by buffer area, and sum up the population by block group.

Next, through careful subtraction of counts and sums, we were able to get the total number of clients and the target population in each ring around facili-ties (such as 0.5 mi, 1 mi, 1.5 mi), calculate use rates for each ring by dividing the count of clients by the sum of the target population, and plot the relationship of use rate versus mean distance of each ring from facilities. We found that the use rate by clients, who were elderly users of the senior center facilities in our county, declined rapidly with distance, presumably because of the seniors’ mobility lim-itations. The policy implication is that senior centers need to be located in areas that have high densities of elderly populations so that more of the elderly will be able to use them. You will conduct similar buffer analyses in chapters 7, 9, and 10 in a variety of health contexts.

Summary of chaptersFollowing is a brief summary of chapters. Chapters 1 – 9 include tutorials for learning GIS and chapters 10 and 11 are optional case studies that reinforce the skills learned in the previous chapters.

Chapter 1: Introducing GIS and health applicationsHealth care is a large, growing, and complex sector of economies around the world. The United States, like other countries, faces many challenges in providing


the best health care for its citizens and at the lowest possible cost. Currently, many health informatics systems are manual and/or nonintegrated (The Economist 2005) in that interacting organizations have in-house information systems that are not connected to each other in ways that would allow beneficial sharing of data. This has led to top-heavy administrations, high costs of transac-tions (Hagland 2004), medical errors, and duplication of efforts, such as unnec-essary medical tests (Protti 2005). Additional health policy issues can arise from too much emphasis on the treatment of sickness and not enough on the pre-vention of illness (Kennedy 2004), enormous numbers of uninsured persons, the overuse of emergency rooms, nursing shortages, and the lack of preparedness for bioterrorism (Featherly 2004).

One clear trend in health policy, research, planning, and management is the increasingly important role of health informatics. More systems will become automated and integrated, at a large cost but with even larger benefits. What does this mean for GIS applications? One consequence is that there will be even more data available for possible input to GIS — additional data on patients, facili-ties, programs, and events that include disease incidence, medical diagnostics, and treatments. Much of the additional data will have street addresses, ZIP Codes, or other location elements that will make it applicable to GIS processing.

In addition to ArcGIS for Desktop, there are online and mobile applications that allow you to view, download, and share basemaps. ArcGIS.com map viewer is a free web application that allows sharing and searching of geographic infor-mation, as well as content published by Esri, ArcGIS users, and other authori-tative data providers. ArcGIS.com map viewer allows users to create and join groups and to control access to items shared publicly or within groups. For those wanting to explore using GIS on mobile devices, ArcGIS for iOS is a free applica-tion that runs on an iOS device such as iPad or iPhone. You can download this free application to your iOS device to view web maps created in ArcGIS Online and perform simple GIS functions such as measuring distances and areas.

In this chapter, you begin to explore the online sites by creating layer packages in ArcMap, one of the primary components of ArcGIS for Desktop, to upload to ArcGIS.com as well as explore health content already available on this website.

The book overall contains a sampling of health GIS applications that cut a wide path across the landscape we have just described.

Chapter 2: Visualizing health dataChapter 2 uses a simple public health application for visualizing breast cancer mortality rates at the state and county levels across the United States. In the tutorials, you work with breast cancer data. While valuable for provid-ing a snapshot of cancer mortality, the primary purpose of the application is to get you comfortable with map navigation in ArcGIS. ArcGIS provides many ways to change scales and views of a map in search of information, as well as ways to work with the data records behind the map features. You will get experience with some of them in this chapter.


Chapter 3: Designing maps for a health studyIn chapter 3, you learn about uninsured populations in a state and their health-care financial needs. In the tutorials, you analyze where to locate programs that provide health-related financial support for uninsured populations in Texas counties. You use an advanced map with a bivariate analysis to contrast the mag-nitude of uninsured populations with measures of poverty by county.

GIS can provide many kinds of outputs. In this chapter, you build stand-alone map layouts that contain components such as multiple map frames, legends, and scale bars for use in presentations and reports.

Chapter 4: Projecting, downloading, and using spatial dataWhat are the most appropriate ways to map disease incidence (numbers of cases) versus prevalence (numbers of cases per population of 10,000)? In the first health application in chapter 4, you visualize a communicable disease — HIV infection and AIDS. You build two kinds of map layers to encode data: one for disease inci-dence based on polygon centroids (points) using size-graduated point markers and the other for disease prevalence represented by the fill color for polygons.

A second application teaches you how to download international HIV/AIDS data from a website for a selected country.

A third application uses local data to pursue the problem of child obesity. Your objective in these tutorials is to identify green spaces in the vicinity of schools that could possibly be used in physical education programs. You will also learn how to download aerial images from USGS.

GIS issues pursued in these applications involve downloading and importing spatial data into ArcGIS and projecting map layers based on the application and geographic scale at hand.

Chapter 5: Downloading and preparing spatial and tabular dataWhere are the concentrations of a city’s older houses that are likely to have lead-based paint? Do children who have elevated levels of lead in their blood live in those areas? The purpose of the study in chapter 5 is to identify clusters of chil-dren who have elevated blood lead levels for the targeting of lead-screening programs. You work with elevated blood lead level samples that have been aggre-gated to census tracts and census tract data on housing built before 1970, when lead-based paints were still used.

In chapter 5, you download and prepare US Census data. You must clean up the data by renaming variables and deleting rows that do not conform to data table formats and by modifying census tract identifiers in the table so that they match comparable identifiers in the census tract map layer. Then you join them to a downloaded census tract boundary map. Ultimately, you will produce a very nice bivariate map using choropleth and dot-density displays. In that map, you will place randomly located points within polygons in proportion to an attribute of


interest. The tutorials in chapter 5 seek additional explanation of observed clusters by using additional census variables to spatially explore a public health problem.

Chapter 6: Geocoding tabular dataGeneral spatial information is available from basemaps, but how do you format the data your organization has so it can be converted to points on a map? Data of interest often includes point locations of patients’ or clients’ residences and health care or other service delivery locations, such as the scenes of traffic acci-dents. If data includes street addresses, ZIP Codes, or other spatial identifiers, GIS has the tools to plot points of interest for use in analysis.

For the example in chapter 6, you need to spatially enable data that is in tabu-lar form. You’ll geocode existing facilities within a county so they can be placed as points on a map. You also place patients on a ZIP Code map over a wide area. Having this data mapped, you can readily see potential service gaps. Then you map suitability measures for a health clinic location to aid in identifying loca-tions in gap areas that would be an attractive site for a new facility.

Chapter 7: Processing and analyzing spatial dataWhat are some neighborhood factors that lead to child pedestrian injuries in a city? Is poverty a factor? What about the lack of safe public areas for play? In chapter 7, you explore the determinants of serious juvenile-pedestrian injuries for the purpose of designing prevention programs. The basis of your study is a sample of serious-injury data that has been geocoded and can be compared to census data on poverty and to map layers for streets, neighborhoods, and parks that have playgrounds and playing fields.

The GIS work in chapter 7 includes preparatory steps for extracting study region maps from county maps, and then focuses on detailed proximity analyses using park buffers, like those seen in figure 1.2.

Chapter 8: Transforming data using approximate methodsHow can health-care analysts combine data from different, incompatible polygon boundary sets? Chapter 8 explores how to transform this data so it can be used for comparative analysis. Often the spatial unit of analysis for a health study is a cus-tom set of polygon boundaries designed for the phenomenon at hand. An exam-ple is the hospital service areas and hospital referral regions used in the Dartmouth Atlas of Health Care Project (http://www.dartmouthatlas.org) at the Center for the Evaluative Clinical Sciences at Dartmouth Medical School in Hanover, New Hamp-shire. Although appropriate for studying patterns in the quality of health care across the country, these custom areas have the limitation of not sharing boundaries with census statistical areas (that is, they are noncoterminous sets of boundaries). Thus, census data cannot be used directly for supportive analysis of these custom areas and must be spatially apportioned to the noncoterminous boundaries.


Another common case of noncoterminous data involves regional analysis of spatial areas such as emergency management service zones for a city where such zones become the de facto unit of spatial analysis. Detailed census variables on income, poverty, educational attainment, and so on are not easily attainable at these levels. Advanced GIS functionality such as using spatial joins, however, can produce some very accurate approximations (or apportionments) for transform-ing data from one set of polygons to another incompatible set.

Chapter 9: Using ArcGIS Spatial Analyst for demand estimationChapter 9 is an introduction to the ArcGIS Spatial Analyst extension. Spatial Analyst uses or creates raster datasets composed of grid cells to display data that is distributed continuously over space as one continuous surface. In this chap-ter, you prepare and analyze a demand surface map for the location of heart defi-brillators in Pittsburgh, where demand is based on the number of out-of-hospital cardiac arrests in which potential bystander help is available. You also learn how to use ArcGIS Spatial Analyst to create a poverty index surface combined with several census data measures from block and block group polygon layers.

Chapter 10: Studying food-borne-disease outbreaksChapters 10 and 11 provide a change of pace — opportunities for you to apply and extend the GIS skills and health applications you have learned in the previous nine chapters to new case studies that you develop. We provide the source data and guidelines for analysis, as well as a broad outline of steps; however, it is up to you to carry out the GIS work on your own in an independent case study. In chap-ter 10, you prepare map layers, including geocoding incidence addresses as the basis for analyzing outbreaks of food-borne illness. Then you use data to simulate the impact of an outbreak. You also do a proximity analysis based on patterns in reported disease cases.

Chapter 11: Forming local chapters of ACHEChapter 11 concludes this workbook with a second independent case study, following a setup similar to that in chapter 10. Staff members of the American College of Healthcare Executives (ACHE) want you to use GIS to help them set up ACHE chapters across the country that provide educational and other services to health-care professionals.

In chapter 11, you perform a buffer analysis of existing affiliates that propose becoming ACHE chapters. The buffers will help determine the territories that are served as well as the gaps that suggest where new chapters should be established. You do some work interactively using ArcGIS, but for steps that must be done repeatedly over time, you build an ArcGIS model that generates a macro to auto-mate these steps.


Introduction to ArcGIS and map documentsThis book is designed for use with ArcGIS 10.2 for Desktop software. ArcGIS is a full-featured GIS software application for visualizing, managing, creating, and analyzing geographic data. The more advanced levels of ArcGIS offer advanced data conversion and geoprocessing capabilities. ArcGIS has numerous extensions that include ArcGIS 3D Analyst for three-dimensional rendering of surfaces, ArcGIS Network Analyst for routing and other street network applications, and ArcGIS Spatial Analyst for generating and working with raster maps.

ArcGIS includes four application programs: ArcCatalog, ArcGlobe, ArcMap, and ArcScene. ArcCatalog is a utility program for file browsing, data importing and converting, and file maintenance functions (such as create, copy, and delete) — all with special features for GIS source data. You will use ArcCatalog instead of the Microsoft Windows utilities My Computer or Windows Explorer to manage GIS source data. ArcGlobe provides 3D capabilities to work seamlessly on a 3D globe. ArcMap is the primary interface for building, viewing, and analyzing conventional two-dimensional (2D) maps. ArcScene is comparable to ArcMap but for 3D maps.

GIS analysts use ArcMap to compose a map from basemap layers, and then carry out many kinds of analysis and produce several types of GIS outputs. A map composition is saved to a map document file and has a name, chosen by the user, and the .mxd file extension. For example, you will soon open the first map docu-ment in the chapter, Tutorial1-3.mxd.

A map document stores pointers (paths) to map layers, data tables, and other data sources for use in a map composition, but it does not store a copy of any data source. Consequently, map layers can be stored anywhere on your computer, local area network, or even on an Internet server, and be part of your map document. In this book, you will use data sources available from the data you will download from the Esri Press “Book Resources” webpage (see the following section).


Exercise data and softwareData for the book is available to download on the Esri Press “Book Resources” webpage, esripress.esri.com/bookresources. Click the appropriate book title, and then click the data link under “Resources” to download the exercise data. A 60-day trial of ArcGIS for Desktop software and extensions is available for readers at esri.com/trydesktop. You must download the data and have access to ArcGIS 10.2 for Desktop software to complete the tutorials in this book.

Learning about ArcGISThe following tutorials will acquaint you with the functionality and user interface of ArcMap and ArcCatalog. You will start by using ArcCatalog to browse through the data sources used in figure 1.1, and then examine the completed project itself. In the remaining chapters, you will learn how to build, modify, and query data.

In the tutorials that follow, you need to be at your computer to carry out the numbered steps. Screen captures accompanying the steps illustrate impor-tant dialog boxes and output. Occasionally, we have added “Your turn” exercises after a series of steps. It is critical that you do these brief exercises to internal-ize the processes covered. Note that the appearance of the user interface is con-tantly changing, depending on your operating system and customization choices, so the windows in this book may not appear exactly like the windows on your screen.

14 Chapter 1: Introducing GIS and health applicationsT

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Tutorial 1-1 Exploring the ArcCatalog user interface1 Start Windows, and then click Start to start your programs. Click All

Programs > ArcGIS > ArcCatalog 10.2. Depending on how ArcGIS has been installed, you may have a different navigation menu or a name other than ArcGIS. The left panel of ArcCatalog is called the Catalog tree. It is used to navigate to the data on your computer or network server, much like Windows Explorer.

2 Use the Connect to Folder tool on the ArcCatalog toolbar to make a connection to the \EsriPress\GISTHealth folder. In the Connect to Folder dialog, browse to GISTHealth and click OK. This will create a connection you will use to navigate to the tutorial data for the rest of this book.

3 In the Catalog tree, browse to \EsriPress\GISTHealth\Data\ by clicking the small plus signs (+) to expand the folders in which the GISTHealth data is installed. The default location for this folder is C:\EsriPress\ GISTHealth\Data, but it may be in a different location depending on where you or your instructor installed it. If you cannot find this folder, make sure it was installed properly.

15Chapter 1: Introducing GIS and health applicationsT 1-1

4 After navigating to the Data folder, expand the United States geodata-base, UnitedStates.gdb. The right panel, called the Catalog display, con-tains three tabs: Contents, Preview, and Description. When you click the Contents tab, the datasets in the current folder are listed. The datasets cur-rently listed represent spatial data, and the icon next to each file name indi-cates what type of geometry the data is built in: point, line, or polygon. (See facing page.)

5 In the Catalog tree, click USStates and click the Preview tab. Previewing data this way allows you to get a quick glimpse of the data without actually loading it into a map. You can also use this tab to preview the contents of a table.


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6 At the bottom of the Catalog display, click the Preview arrow, click Table, and then use the horizontal scroll bar to view the attribute fields in the table. Each record in the table corresponds to one of the state polygons you previewed in the preceding step, and as you can see, there are quite a few attri-butes stored for each state, most of which are demographic. For example, by reading across the table, you could identify that the state of Washington is in the Pacific subregion and had a population of 5,894,121 in 2000 and 6,756,150 in 2010. We used the STATE_NAME attribute to label states in figure 1.1.


7 Click the Description tab at the top of the Catalog display. This tab describes metadata, which is data about data. T 1-1


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8 In the Catalog display, click the Contents tab.

Other folders in the \EsriPress\GISTHealth\ Catalog tree include Maps, where original map document files are located; MyAssignments, where you will save files to chapter folders if you are working in a classroom and are required to complete the assignments at the end of each chapter; and MyExercises, where you will save files as you complete tutorial exercises in each chapter. MyExercises contains a subfolder called FinishedExercises, which includes tutorial exercises completed by the book’s authors that you can use as needed.

Explore additional layers in UnitedStates.gdb. When you are finished, click the tog-

gle key that has the minus sign (-) to the left of the UnitedStates.gdb folder icon in

the Catalog tree to collapse that folder. Then close ArcCatalog.

Chapter 1 · Chapter 1: Introducing GIS and health applications 5 Digital map infrastructure GIS is...

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Transcript of Chapter 1 · Chapter 1: Introducing GIS and health applications 5 Digital map infrastructure GIS is...